[Li, Wanting; Yang, Jingyu; Peng, Li; Yang, Tongguang] Hunan City Univ, Key Lab Smart City Energy Sensing & Edge Comp Huna, Yiyang 413000, Peoples R China.
通讯机构：
[Li, WT ] H
Hunan City Univ, Key Lab Smart City Energy Sensing & Edge Comp Huna, Yiyang 413000, Peoples R China.
语种：
英文
关键词：
Meteorology;Wind power generation;Predictive models;Accuracy;Wind turbines;Wind forecasting;Wind speed;Rain;Fluctuations;Atmospheric modeling;Deep learning;extreme weather;Kernel density estimation;time GAN;wind power prediction
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 52377181)
Excellent Youth Program of Hunan Provincial Department of Education (Grant Number: 23B0745)
Hunan Provincial Natural Science Foundation Project (Grant Number: 2024JJ7088)
Project of Natural Science Foundation of Hunan Province (Grant Number: 2023JJ50344)
机构署名：
本校为第一且通讯机构
摘要：
The prediction of wind power generation is an important basis for the rational scheduling of new energy sources in wind power. However, the severe fluctuations in wind power output under extreme weather conditions pose a serious challenge for ultra-short-term wind power output prediction. A combination forecasting method for ultra-short-term wind power that comprehensively considers extreme weather and normal weather is proposed to address the above issues. To explore the differences in power time series characteristics under different scenarios in terms of the relationships between wind power...
